Under some approaches, a platform for analyzing various data may be deployed. The data-analysis platform may support an object-based data modeling framework. Frequently, data may be collected in a tabular format. Importing tabular formatted data into an object-based data modeling platform may require applying the ontology of the object-based data platform to a tabular data set to transform the tabular data set into data that conforms as required for the object-based data modeling platform. Applying the ontology may require cleaning the data, applying a script to it, and then checking the results. Applying the script to the data may be a time consuming process, as the original data set may include millions or billions of data rows. Even small errors in the data transformation script may result in a failure of the data transformation. Such a failure may not be noticed until after the script has finished running, resulting in a significant waste of time and resources.
These and other drawbacks exist with conventional data management systems.